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57dbc1b @rkern Fleshed-out site.cfg example.
rkern authored
1 # This file provides configuration information about non-Python dependencies for
2 # numpy.distutils-using packages. Create a file like this called "site.cfg" next
3 # to your package's setup.py file and fill in the appropriate sections. Not all
4 # packages will use all sections so you should leave out sections that your
5 # package does not use.
6
f13e905 @rkern Add another place to check for configuration, namely ~/.numpy-site.cf…
rkern authored
7 # To assist automatic installation like easy_install, the user's home directory
8 # will also be checked for the file ~/.numpy-site.cfg .
9
57dbc1b @rkern Fleshed-out site.cfg example.
rkern authored
10 # The format of the file is that of the standard library's ConfigParser module.
11 #
12 # http://www.python.org/doc/current/lib/module-ConfigParser.html
13 #
14 # Each section defines settings that apply to one particular dependency. Some of
15 # the settings are general and apply to nearly any section and are defined here.
16 # Settings specific to a particular section will be defined near their section.
17 #
18 # libraries
19 # Comma-separated list of library names to add to compile the extension
20 # with. Note that these should be just the names, not the filenames. For
21 # example, the file "libfoo.so" would become simply "foo".
22 # libraries = lapack,f77blas,cblas,atlas
23 #
24 # library_dirs
25 # List of directories to add to the library search path when compiling
26 # extensions with this dependency. Use the character given by os.pathsep
27 # to separate the items in the list. On UN*X-type systems (Linux, FreeBSD,
28 # OS X):
29 # library_dirs = /usr/lib:/usr/local/lib
30 # On Windows:
31 # library_dirs = c:\mingw\lib,c:\atlas\lib
32 #
33 # include_dirs
34 # List of directories to add to the header file earch path.
35 # include_dirs = /usr/include:/usr/local/include
36 #
37 # src_dirs
38 # List of directories that contain extracted source code for the
39 # dependency. For some dependencies, numpy.distutils will be able to build
40 # them from source if binaries cannot be found. The FORTRAN BLAS and
41 # LAPACK libraries are one example. However, most dependencies are more
42 # complicated and require actual installation that you need to do
43 # yourself.
44 # src_dirs = /home/rkern/src/BLAS_SRC:/home/rkern/src/LAPACK_SRC
45 #
46 # search_static_first
47 # Boolean (one of (0, false, no, off) for False or (1, true, yes, on) for
48 # True) to tell numpy.distutils to prefer static libraries (.a) over
49 # shared libraries (.so). It is turned off by default.
50 # search_static_first = false
51
52 # Defaults
53 # ========
54 # The settings given here will apply to all other sections if not overridden.
55 # This is a good place to add general library and include directories like
56 # /usr/local/{lib,include}
57 #
58 #[DEFAULT]
59 #library_dirs = /usr/local/lib
60 #include_dirs = /usr/local/include
61
62 # Optimized BLAS and LAPACK
63 # -------------------------
64 # Use the blas_opt and lapack_opt sections to give any settings that are
65 # required to link against your chosen BLAS and LAPACK, including the regular
66 # FORTRAN reference BLAS and also ATLAS. Some other sections still exist for
67 # linking against certain optimized libraries (e.g. [atlas], [lapack_atlas]),
68 # however, they are now deprecated and should not be used.
69 #
70 # These are typical configurations for ATLAS (assuming that the library and
71 # include directories have already been set in [DEFAULT]; the include directory
72 # is important for the BLAS C interface):
73 #
74 #[blas_opt]
75 #libraries = f77blas, cblas, atlas
76 #
77 #[lapack_opt]
78 #libraries = lapack, f77blas, cblas, atlas
79 #
80 # If your ATLAS was compiled with pthreads, the names of the libraries might be
81 # different:
82 #
83 #[blas_opt]
84 #libraries = ptf77blas, ptcblas, atlas
85 #
86 #[lapack_opt]
87 #libraries = lapack, ptf77blas, ptcblas, atlas
88
89 # UMFPACK
90 # -------
91 # The UMFPACK library is used to factor large sparse matrices. It, in turn,
92 # depends on the AMD library for reordering the matrices for better performance.
93 # Note that the AMD library has nothing to do with AMD (Advanced Micro Devices),
94 # the CPU company.
95 #
96 # http://www.cise.ufl.edu/research/sparse/umfpack/
97 # http://www.cise.ufl.edu/research/sparse/amd/
98 #
99 #[amd]
100 #amd_libs = amd
101 #
102 #[umfpack]
103 #umfpack_libs = umfpack
104
105 # FFT libraries
106 # -------------
107 # There are two FFT libraries that we can configure here: FFTW (2 and 3) and djbfft.
108 #
109 # http://fftw.org/
110 # http://cr.yp.to/djbfft.html
111 #
112 # Given only this section, numpy.distutils will try to figure out which version
113 # of FFTW you are using.
114 #[fftw]
115 #libraries = fftw3
116 #
117 # For djbfft, numpy.distutils will look for either djbfft.a or libdjbfft.a .
118 #[djbfft]
119 #include_dirs = /usr/local/djbfft/include
120 #library_dirs = /usr/local/djbfft/lib
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